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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Large-Scale Molecular Dynamics Simulation Studies on Deformation of Ni Nanowires: Surface Profile, Defects and Stacking Fault Width Analysis

We report large-scale molecular dynamics simulation deformation studies of Ni nanowire (NW) of size 100 Å (x) × 1000 Å (y) × 100 Å (z) comprising of 925,965 atoms. Surface and internal defects are introduced to study their effect on the surface profile, strength, fracture behavior and deformation mechanisms. Tensile tests have been carried out at a temperature of 10 K and at a strain rate of 10{sup 8} s{sup −1}. Periodic boundary condition is applied along the loading direction (y). Peak strength of 23 GPa is observed in the perfect NW, and the strength decreases with defects. The surface profiles of the deformed NWs show intrusion and extrusion regions corresponding to slip steps with wider valleys in the defect NWs. Several intrinsic and extrinsic parallel stacking faults (SFs) are generated after yielding by slip occurring on {111} planes. The calculated SF widths are in the range of 0.85-2.57 nm in the perfect NW. The dislocations are mainly Shockley partial dislocations of type 1/6 〈112〉, and Schmid’s factor (m) obtained is 0.471. Twinning dislocation of types 1/9 〈221〉 and 1/18 〈172〉 is also observed in the SFs. The density of Shockley partial dislocations is observed to be the maximum in all the NWs.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Validation of SCALE for High Temperature Gas-Cooled Reactors Analysis

This report documents verification and validation studies carried out to assess the performance of the SCALE code system methods and nuclear data for modeling and analysis of High Temperature Gas-Cooled Reactor (HTGR) configurations. Validation data were available from the International Handbook of Evaluated Reactor Physics Benchmark Experiments (IRPhE Handbook), prepared by the International Reactor Physics Experiment Evaluation Project, for two different HTGR designs: prismatic and pebble bed. SCALE models have been developed for HTTR, a prismatic fuel design reactor operated in Japan and HTR-10, a pebble bed reactor operated in China. The models were based on benchmark specifications included in the 2009, 2010, and 2011 releases of the IRPhE Handbook. SCALE models for the HTR-PROTEUS pebble bed configuration at the PROTEUS critical facility in Switzerland have also been developed, based on benchmark specifications included in a 2009 IRPhE draft benchmark. The development of the SCALE models has involved a series of investigations to identify particular issues associated with modeling the physics of HTGRs and to understand and quantify the effect of particular modeling assumptions on calculation-to-experiment comparisons.

Ilas, Germina↗
DOE OSTI2014

Hybrid methods for cybersecurity analysis :

Early 2010 saw a signi cant change in adversarial techniques aimed at network intrusion: a shift from malware delivered via email attachments toward the use of hidden, embedded hyperlinks to initiate sequences of downloads and interactions with web sites and network servers containing malicious software. Enterprise security groups were well poised and experienced in defending the former attacks, but the new types of attacks were larger in number, more challenging to detect, dynamic in nature, and required the development of new technologies and analytic capabilities. The Hybrid LDRD project was aimed at delivering new capabilities in large-scale data modeling and analysis to enterprise security operators and analysts and understanding the challenges of detection and prevention of emerging cybersecurity threats. Leveraging previous LDRD research e orts and capabilities in large-scale relational data analysis, large-scale discrete data analysis and visualization, and streaming data analysis, new modeling and analysis capabilities were quickly brought to bear on the problems in email phishing and spear phishing attacks in the Sandia enterprise security operational groups at the onset of the Hybrid project. As part of this project, a software development and deployment framework was created within the security analyst work ow tool sets to facilitate the delivery and testing of new capabilities as they became available, and machine learning algorithms were developed to address the challenge of dynamic threats. Furthermore, researchers from the Hybrid project were embedded in the security analyst groups for almost a full year, engaged in daily operational activities and routines, creating an atmosphere of trust and collaboration between the researchers and security personnel. The Hybrid project has altered the way that research ideas can be incorporated into the production environments of Sandias enterprise security groups, reducing time to deployment from months and years to hours and days for the application of new modeling and analysis capabilities to emerging threats. The development and deployment framework has been generalized into the Hybrid Framework and incor- porated into several LDRD, WFO, and DOE/CSL projects and proposals. And most importantly, the Hybrid project has provided Sandia security analysts with new, scalable, extensible analytic capabilities that have resulted in alerts not detectable using their previous work ow tool sets.

Dunlavy, Daniel M.↗
DOE OSTI2021

SCALE 6.2.4 Validation for Light Water Reactor Decay Heat Analysis

Energy release from the decay of radionuclides in nuclear fuel after its discharge from reactor is a critical parameter for design, safety, and licensing analyses of used nuclear fuel storage, transportation, and repository systems. Well-validated computational tools and nuclear data are essential for decay heat prediction. This paper summarizes the validation of the SCALE nuclear analysis code system version 6.2.4, used with ENDF/B-VII.1 libraries, for decay heat analysis of light water reactor used fuel. The experimental data used for validation include full-assembly decay heat measurements that cover assembly burnups of 5 to 51 GWd/tonne U, cooling times after discharge in the 2- to 27-year range, and initial fuel enrichments up to 4 wt% 235U. The comparison between calculated (C) and experimental (E) decay heat showed very good agreement, with an average C/E over all considered measurements of 1.006 (σ = 0.016) for pressurized water reactor and 0.984 (σ = 0.077) for boiling water reactor assembly measurements. The effect of using assembly-average versus axially varying modeling data on the calculated decay heat, important to thermal analyses for used fuel transportation and storage systems, is discussed.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2012

NIBBS-Search for Fast and Accurate Prediction of Phenotype-Biased Metabolic Systems

Understanding of genotype-phenotype associations is important not only for furthering our knowledge on internal cellular processes, but also essential for providing the foundation necessary for genetic engineering of microorganisms for industrial use (e.g., production of bioenergy or biofuels). However, genotype-phenotype associations alone do not provide enough information to alter an organism’s genome to either suppress or exhibit a phenotype. It is important to look at the phenotype-related genes in the context of the genome-scale network to understand how the genes interact with other genes in the organism. Identification of metabolic subsystems involved in the expression of the phenotype is one way of placing the phenotype-related genes in the context of the entire network. A metabolic system refers to a metabolic network subgraph; nodes are compounds and edges labels are the enzymes that catalyze the reaction. The metabolic subsystem could be part of a single metabolic pathway or span parts of multiple pathways. Arguably, comparative genome-scale metabolic network analysis is a promising strategy to identify these phenotype-related metabolic subsystems. Network Instance-Based Biased Subgraph Search (NIBBS) is a graph-theoretic method for genome-scale metabolic network comparative analysis that can identify metabolic systems that are statistically biased toward phenotypeexpressing organismal networks. We set up experiments with target phenotypes like hydrogen production, TCA expression, and acid-tolerance. We show via extensive literature search that some of the resulting metabolic subsystems are indeed phenotype-related and formulate hypotheses for other systems in terms of their role in phenotype expression. NIBBS is also orders of magnitude faster than MULE, one of the most efficient maximal frequent subgraph mining algorithms that could be adjusted for this problem. Also, the set of phenotype-biased metabolic systems output by NIBBS comes very close to the set of phenotype-biased subgraphs output by an exact maximally-biased subgraph enumeration algorithm ( MBS-Enum ). The code (NIBBS and the module to visualize the identified subsystems) is available at http:// freescience.org/cs/NIBBS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Computation of Effective Mechanical Properties and Mechanical Erosion Modeling of TPS Materials

The goal of this presentation is to provide a general overview of the multi-scale modeling formulation to determine if there is additional surface recession in Thermal Protection Systems (TPS) materials as a result of mechanical erosion due to high shear conditions during atmospheric entry. This modeling process is performed at different scales by leveraging two computational frameworks developed at NASA: the Porous Microstructure Analysis (PuMA) software, and the Porous material Analysis Toolbox based on OpenFOAM (PATO). PuMA specializes in computing effective macro-scale material properties by performing material response simulations on 3D digital micro-scale representations of porous micro-structures. The modeling of TPS materials at the micro-scale is essential to understand how they behave as part of a heat shield assembly. The first part of the presentation will detail the implementation of PuMA’s cell-centered finite volume elasticity solver, which allows the computation of macro-scale effective mechanical properties of heterogeneous and anisotropic materials such as fibrous and woven TPS composites. These homogenized mechanical properties are used by PATO’s mechanical erosion model to predict the TPS material’s recession at a larger scale. This work will also provide some examples of multi-scale analysis from the fiber level up to the unit cell. The second part of the presentation will focus on the macro-scale approach to determine if erosion at the heat shield’s surface occurs due to mechanical and thermal loads experienced during atmospheric entry. To accomplish this, a solid mechanics module was integrated within PATO enabling it to model the potential mechanical erosion in three steps: first, after obtaining the effective mechanical properties with PuMA, the implemented stress analysis solver computes the stress and the displacement fields for the TPS material using the wall shear stress tensor, computed using a CFD solver, as boundary conditions; then, regions on the surface where the stress meets the failure criteria are identified; finally, the failed material is removed and the mesh is redistributed accordingly. The outcome is a model capable of predicting the total recession in the material due to surface chemistry and mechanical erosion.

Mechanical Properties↗
NASA NTRS2020

Design and Analysis of Buckling-Critical Large-Scale Sandwich Composite Cylindrical Test Articles

It has long been established in the literature that the buckling response of thin-shell structures can be very sensitive to the presence of small geometric and loading imperfections. The Shell Buckling Knockdown Factor Project (SBKF) was established by the NASA Engineering and Safety Center (NESC) to develop analysis-based shell buckling design recommendations for stiffened-metallic and composite launch-vehicle shell structures. Large-scale buckling tests were used to validate the modeling and analysis methods applied in developing these analysis-based recommendations. Herein, the test article design methodology for 8-ft-diameter, honeycomb-core sandwich composite cylinder validation tests is discussed and cylinder designs are presented. In this methodology, first, the sandwich composite design space was defined using several nondimensional parameters, and the desired test article design space was determined by examining the designs of launch-vehicle cylinder structures. Essentially all test article designs within certain design parameters were generated and then downselected based on simple closed-form failure calculations and the nondimensional design-space parameters. Four of these designs that spanned a significant portion of the design space of interest and had global buckling as the first predicted failure mode were selected and subjected to higher-fidelity finite element analyses (FEAs): shell-element-based analyses, axisymmetric-element-based analyses, and global-local analyses. The analysis flow discussed in this report supported the design objective. As the analysis flow progressed, designs were downselected so the fidelity of the analysis methods, and consequently their computational cost and accuracy, was increased. The selection of the FEA types created an analysis framework where particular methods complemented each other and reduced the uncertainty of the predicted test article responses. The analysis results are illustrated using several designs when the computationally expeditious closed-form analysis stage is discussed. Once this stage is complete, the higher-fidelity FEA types are illustrated using one selected detailed test article design. Both perfect and imperfect test article geometries were considered.

Buckling↗
DOE OSTI2021

Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances, Weak Lensing, and Galaxy Correlations

We present the first joint analysis of cluster abundances and auto or cross-correlations of three cosmic tracer fields: galaxy density, weak gravitational lensing shear, and cluster density split by optical richness. From a joint analysis (4×2pt+N) of cluster abundances, three cluster cross-correlations, and the auto correlations of the galaxy density measured from the first year data of the Dark Energy Survey, we obtain Ωm=0.305-0.038+0.055 and σ8=0.783-0.054+0.064. This result is consistent with constraints from the DES-Y1 galaxy clustering and weak lensing two-point correlation functions for the flat νΛCDM model. Consequently, we combine cluster abundances and all two-point correlations from across all three cosmic tracer fields (6×2pt+N) and find improved constraints on cosmological parameters as well as on the cluster observable-mass scaling relation. This analysis is an important advance in both optical cluster cosmology and multiprobe analyses of upcoming wide imaging surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Life Cycle Water Consumption and Water Resource Assessment for Utility-Scale Geothermal Systems: An In-Depth Analysis of Historical and Forthcoming EGS Projects

This report is the third in a series of reports sponsored by the U.S. Department of Energy Geothermal Technologies Program in which a range of water-related issues surrounding geothermal power production are evaluated. The first report made an initial attempt at quantifying the life cycle fresh water requirements of geothermal power-generating systems and explored operational and environmental concerns related to the geochemical composition of geothermal fluids. The initial analysis of life cycle fresh water consumption of geothermal power-generating systems identified that operational water requirements consumed the vast majority of water across the life cycle. However, it relied upon limited operational water consumption data and did not account for belowground operational losses for enhanced geothermal systems (EGSs). A second report presented an initial assessment of fresh water demand for future growth in utility-scale geothermal power generation. The current analysis builds upon this work to improve life cycle fresh water consumption estimates and incorporates regional water availability into the resource assessment to improve the identification of areas where future growth in geothermal electricity generation may encounter water challenges. This report is divided into nine chapters. Chapter 1 gives the background of the project and its purpose, which is to assess the water consumption of geothermal technologies and identify areas where water availability may present a challenge to utility-scale geothermal development. Water consumption refers to the water that is withdrawn from a resource such as a river, lake, or nongeothermal aquifer that is not returned to that resource. The geothermal electricity generation technologies evaluated in this study include conventional hydrothermal flash and binary systems, as well as EGSs that rely on engineering a productive reservoir where heat exists, but where water availability or permeability may be limited. Chapter 2 describes the approach and methods for this work and identifies the four power plant scenarios evaluated: a 20-MW EGS binary plant, a 50-MW EGS binary plant, a 10-MW hydrothermal binary plant, and a 50-MW hydrothermal flash plant. The methods focus on (1) the collection of data to improve estimation of EGS stimulation volumes, aboveground operational consumption for all geothermal technologies, and belowground operational consumption for EGS; and (2) the mapping of the geothermal and water resources of the western United States to assist in the identification of potential water challenges to geothermal growth. Chapters 3 and 4 present the water requirements for the power plant life cycle. Chapter 3 presents the results of the current data collection effort, and Chapter 4 presents the normalized volume of fresh water consumed at each life cycle stage per lifetime energy output for the power plant scenarios evaluated. Over the life cycle of a geothermal power plant, from construction through 30 years of operation, the majority of water is consumed by plant operations. For the EGS binary scenarios, where dry cooling was assumed, belowground operational water loss is the greatest contributor depending upon the physical and operational conditions of the reservoir. Total life cycle water consumption requirements for air-cooled EGS binary scenarios vary between 0.22 and 1.85 gal/kWh, depending upon the extent of belowground operational water consumption. The air-cooled hydrothermal binary and flash plants experience far less fresh water consumption over the life cycle, at 0.04 gal/kWh. Fresh water requirements associated with air- cooled binary operations are primarily from aboveground water needs, including dust control, maintenance, and domestic use. Although wet-cooled hydrothermal flash systems require water for cooling, these plants generally rely upon the geofluid, fluid from the geothermal reservoir, which typically has high salinity and total dissolved solids concentration and is much warmer than normal groundwater sources, for their cooling water needs; thus, while there is considerable geofluid loss at 2.7 gal/kWh, fresh water consumption during operations is similar to that of aircooled binary systems. Chapter 5 presents the assessment of water demand for future growth in deployment of utility-scale geothermal power generation. The approach combines the life cycle analysis of geothermal water consumption with a geothermal supply curve according to resource type, levelized cost of electricity (LCOE), and potential growth scenarios. A total of 17 growth scenarios were evaluated. In general, the scenarios that assumed lower costs for EGSs as a result of learning and technological improvements resulted in greater geothermal potential, but also significantly greater water demand due to the higher water consumption by EGSs. It was shown, however, that this effect could be largely mitigated if nonpotable water sources were used for belowground operational water demands. The geographical areas that showed the highest water demand for most growth scenarios were southern and northern California, as well as most of Nevada. In addition to water demand by geothermal power production, Chapter 5 includes data on water availability for geothermal development areas. A qualitative analysis is included that identifies some of the basins where the limited availability of water is most likely to affect the development of geothermal resources. The data indicate that water availability is fairly limited, especially under drought conditions, in most of the areas with significant near- and medium-term geothermal potential. Southern California was found to have the greatest potential for water-related challenges with its combination of high geothermal potential and limited water availability. The results of this work are summarized in Chapter 6. Overall, this work highlights the importance of utilizing dry cooling systems for binary and EGS systems and minimizing fresh water consumption throughout the life cycle of geothermal power development. The large resource base for EGSs represents a major opportunity for the geothermal industry; however, depending upon geology, these systems can require large quantities of makeup water due to belowground reservoir losses. Identifying potential sources of compatible degraded or low-quality water for use for makeup injection for EGS and flash systems represents an important opportunity to reduce the impacts of geothermal development on fresh water resources. The importance of identifying alternative water sources for geothermal systems is heightened by the fact that a large fraction of the geothermal resource is located in areas already experiencing water stress. Chapter 7 is a glossary of the technical terms used in the report, and Chapters 8 and 9 provide references and a bibliography, respectively.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Block segmentation in feature space for realtime object detection in high granularity images

Computer vision has applications in object detection, image recognition and classification, and object tracking. One of the challenges of computer vision is the presence of useful information at multiple distance scales. Filtering techniques may sacrifice details at small scales in order to prioritize the analysis of large-scale features of the image. We present a strategy for coarse-graining multidimensional data while maintaining fine-grained detail for subsequent analysis. The algorithm is based on fixed-size block segmentation in the feature space. We apply this strategy to solve the long-standing challenge of detecting particle trajectories at the Large Hadron Collider in real time.

Computer vision↗
DOE OSTI2018

Genomic insights into the Acidobacteria reveal strategies for their success in terrestrial environments

Summary Members of the phylum Acidobacteria are abundant and ubiquitous across soils. We performed a large‐scale comparative genome analysis spanning subdivisions 1, 3, 4, 6, 8 and 23 ( n = 24) with the goal to identify features to help explain their prevalence in soils and understand their ecophysiology. Our analysis revealed that bacteriophage integration events along with transposable and mobile elements influenced the structure and plasticity of these genomes. Low‐ and high‐affinity respiratory oxygen reductases were detected in multiple genomes, suggesting the capacity for growing across different oxygen gradients. Among many genomes, the capacity to use a diverse collection of carbohydrates, as well as inorganic and organic nitrogen sources (such as via extracellular peptidases), was detected – both advantageous traits in environments with fluctuating nutrient environments. We also identified multiple soil acidobacteria with the potential to scavenge atmospheric concentrations of H 2 , now encompassing mesophilic soil strains within the subdivision 1 and 3, in addition to a previously identified thermophilic strain in subdivision 4. This large‐scale acidobacteria genome analysis reveal traits that provide genomic, physiological and metabolic versatility, presumably allowing flexibility and versatility in the challenging and fluctuating soil environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

A hybrid procedure for MSW generation forecasting at multiple time scales in Xiamen City, China

Highlights: ► We propose a hybrid model that combines seasonal SARIMA model and grey system theory. ► The model is robust at multiple time scales with the anticipated accuracy. ► At month-scale, the SARIMA model shows good representation for monthly MSW generation. ► At medium-term time scale, grey relational analysis could yield the MSW generation. ► At long-term time scale, GM (1, 1) provides a basic scenario of MSW generation. - Abstract: Accurate forecasting of municipal solid waste (MSW) generation is crucial and fundamental for the planning, operation and optimization of any MSW management system. Comprehensive information on waste generation for month-scale, medium-term and long-term time scales is especially needed, considering the necessity of MSW management upgrade facing many developing countries. Several existing models are available but of little use in forecasting MSW generation at multiple time scales. The goal of this study is to propose a hybrid model that combines the seasonal autoregressive integrated moving average (SARIMA) model and grey system theory to forecast MSW generation at multiple time scales without needing to consider other variables such as demographics and socioeconomic factors. To demonstrate its applicability, a case study of Xiamen City, China was performed. Results show that the model is robust enough to fit and forecast seasonal and annual dynamics of MSW generation at month-scale, medium- and long-term time scales with the desired accuracy. In the month-scale, MSW generation in Xiamen City will peak at 132.2 thousand tonnes in July 2015 – 1.5 times the volume in July 2010. In the medium term, annual MSW generation will increase to 1518.1 thousand tonnes by 2015 at an average growth rate of 10%. In the long term, a large volume of MSW will be output annually and will increase to 2486.3 thousand tonnes by 2020 – 2.5 times the value for 2010. The hybrid model proposed in this paper can enable decision makers to develop integrated policies and measures for waste management over the long term.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Self-calibrating optical galaxy cluster selection bias using cluster, galaxy, and shear cross-correlations

ABSTRACT The clustering signals of galaxy clusters are powerful tools for self-calibrating the mass–observable relation and are complementary to cluster abundance and lensing. In this work, we explore the possibility of combining three correlation functions – cluster lensing, the cluster–galaxy cross-correlation function, and the galaxy autocorrelation function – to self-calibrate optical cluster selection bias, the boosted clustering and lensing signals in a richness-selected sample mainly caused by projection effects. We develop mock catalogues of redMaGiC-like galaxies and redMaPPer-like clusters by applying halo occupation distribution models to N-body simulations and using counts-in-cylinders around massive haloes as a richness proxy. In addition to the previously known small-scale boost in projected correlation functions, we find that the projection effects also significantly boost three-dimensional correlation functions to scales of 100 $h^{-1} \, \rm Mpc$. We perform a likelihood analysis assuming survey conditions similar to the Dark Energy Survey and show that the selection bias can be self-consistently constrained at the 10 per cent level. We discuss strategies for applying this approach to real data. We expect that expanding the analysis to smaller scales and using deeper lensing data would further improve the constraints on cluster selection bias.

Astronomy & Astrophysics↗
NASA NTRS1988

Interpreting forest biome productivity and cover utilizing nested scales of image resolution and biogeographical analysis

The objective was to relate spectral imagery of varying resolution with ground-based data on forest productivity and cover, and to create models to predict regional estimates of forest productivity and cover with a quantifiable degree of accuracy. A three stage approach was outlined. In the first stage, a model was developed relating forest cover or productivity to TM surface reflectance values (TM/FOREST models). The TM/FOREST models were more accurate when biogeographic information regarding the landscape was either used to stratigy the landscape into more homogeneous units or incorporated directly into the TM/FOREST model. In the second stage, AVHRR/FOREST models that predicted forest cover and productivity on the basis of AVHRR band values were developed. The AVHRR/FOREST models had statistical properties similar to or better than those of the TM/FOREST models. In the third stage, the regional predictions were compared with the independent U.S. Forest Service (USFS) data. To do this regional forest cover and forest productivity maps were created using AVHRR scenes and the AVHRR/FOREST models. From the maps the county values of forest productivity and cover were calculated. It is apparent that the landscape has a strong influence on the success of the approach. An approach of using nested scales of imagery in conjunction with ground-based data can be successful in generating regional estimates of variables that are functionally related to some variable a sensor can detect.

Iverson, Louis R.↗
DOE OSTI2015

High performance discharges in the Lithium Tokamak eXperiment with liquid lithium walls

The first-ever successful operation of a tokamak with a large area (40% of the total plasma surface area) liquid lithium wall has been achieved in the Lithium Tokamak eXperiment (LTX). These results were obtained with a new, electron beam-based lithium evaporation system, which can deposit a lithium coating on the limiting wall of LTX in a five-minute period. Preliminary analyses of diamagnetic and other data for discharges operated with a liquid lithium wall indicate that confinement times increased by 10× compared to discharges with helium-dispersed solid lithium coatings. Ohmic energy confinement times with fresh lithium walls, solid and liquid, exceed several relevant empirical scaling expressions. Spectroscopic analysis of the discharges indicates that oxygen levels in the discharges limited on liquid lithium walls were significantly reduced compared to discharges limited on solid lithium walls. Tokamak operations with a full liquid lithium wall (85% of the total plasma surface area) have recently started.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Oxidation Resistance of Ti-Al-Cr-Nb-Based High-Entropy Alloys in Air at 1073 K

The effects of prolonged exposure to air at 1073 K on Al20Cr25Nb20Ti20Zr15 and Al20Cr25Nb19Ti20Zr15Y1 (at.%) high-entropy alloys (HEAs) were investigated in this work. Combined scanning electron microscopy and energy-dispersive x-ray spectroscopy (SEM–EDS) analysis revealed that scales containing all major elements in the systems are formed during the oxidation process. Thermogravimetric analysis carried out under the above-mentioned corrosive conditions indicates an initial parabolic kinetics course in the case of the sample with 1 at.% Y addition. However, after a certain period of time, the correlation between mass gain per unit surface area and time becomes linear. In the other case, oxidation proceeds according to the parabolic rate law for the entire process duration. The addition of 1 at.% Y decreases the parabolic rate constants by 1 order of magnitude, thereby improving the chemical stability of the studied Al-Cr-Nb-Ti-Zr system. This is confirmed by visual evaluation, as well as SEM–EDS cross-sectional analysis. Additionally, x-ray diffraction studies indicate that a multiphase oxide scale is formed on the metallic core of both samples. This means that selective oxidation does not occur and all constituent elements took part in the reaction. Taking all of the above into account, it can be concluded that more research is required to fully understand and improve the corrosion resistance of Ti-Al-Cr-Nb-based HEAs.

36 MATERIALS SCIENCE↗
DOE OSTI2011

Large Scale Duty Cycle (LSDC) Project: Tractive Energy Analysis Methodology and Results from Long-Haul Truck Drive Cycle Evaluations

This report addresses the approach that will be used in the Large Scale Duty Cycle (LSDC) project to evaluate the fuel savings potential of various truck efficiency technologies. The methods and equations used for performing the tractive energy evaluations are presented and the calculation approach is described. Several representative results for individual duty cycle segments are presented to demonstrate the approach and the significance of this analysis for the project. The report is divided into four sections, including an initial brief overview of the LSDC project and its current status. In the second section of the report, the concepts that form the basis of the analysis are presented through a discussion of basic principles pertaining to tractive energy and the role of tractive energy in relation to other losses on the vehicle. In the third section, the approach used for the analysis is formalized and the equations used in the analysis are presented. In the fourth section, results from the analysis for a set of individual duty cycle measurements are presented and different types of drive cycles are discussed relative to the fuel savings potential that specific technologies could bring if these drive cycles were representative of the use of a given vehicle or trucking application. Additionally, the calculation of vehicle mass from measured torque and speed data is presented and the accuracy of the approach is demonstrated.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Assessment of HRA method predictions against operating crew performance: Part II: Overall simulator data, HRA method predictions, and intra-method comparisons

This is the third in a series of four papers documenting two large-scale human reliability analysis (HRA) empirical studies – the International HRA Empirical Study and the US HRA Empirical Study. Here, the goal of the two studies was to develop an empirically-based understanding of the performance, strengths, and weaknesses of HRA methods by comparing HRA method predictions against actual operator performance in simulated accident scenarios on nuclear power plant (NPP) simulators. However, since in most cases only a single HRA team applied a given method in the International study, it was often difficult to separate analyst effects from variability in results related to the methods themselves. Since at least two HRA teams used each of the HRA methods in the US Study, intra-method comparisons were performed to identify method strengths and weaknesses independent of analyst specific effects where possible. This paper first summarizes the intra-method comparison results from the U.S. Study. Then, it discusses the reasons for the observed HRA predictive differences and the underlying methodological and guidance limitations that permitted the differences to arise. In the fourth paper, this information is combined wit h the results of the comparisons of method predictions to the actual crew data, from both the International and U.S. Studies, to develop the final conclusions about overall strengths and weaknesses of HRA methods.

97 MATHEMATICS AND COMPUTING↗